Data Engineer (SQL/NoSQL, Python, GCP)

Job description

The Data Engineer will architect, build, and operate a data infrastructure that ingests, cleans, integrates, models, and serves data from all restaurant systems—POS/iPOS, inventory, HRM, CRM, online orders, reservations, and external APIs. This role will drive data-driven decision-making by ensuring reliable, timely, and governed datasets for reporting, forecasting, and automation across our multi-location restaurant chain.

Key Responsibilities

• Data Ingestion: Design and implement robust connectors and pipelines to ingest batch and streaming data from POS/iPOS, inventory management, HRM, CRM, online ordering platforms, reservation systems, delivery APIs, social media, and economic-indicator feeds.
• Data Cleaning & Validation: Define and automate data quality checks, reconciliation routines, schema versioning, and master-data governance to ensure accuracy and consistency.
• Data Modeling: Develop dimensional and data-mesh models optimized for analytics, forecasting (sales, staffing, inventory), and operational automation (reordering, dynamic pricing, capacity planning).
• Pipeline Development & Maintenance: Build, document, and monitor resilient ETL/ELT workflows (e.g., Airflow, dbt) with observability, alerting, and automated remediation for batch and near-real-time processing.
• Integration & Delivery: Expose curated datasets to BI tools (e.g., Looker, Power BI), ML platforms, and automation engines; manage APIs and data marts for cross-functional use.

Your skills and experience

• 3+ years in data engineering or similar roles, with at least 1 years building and owning end-to-end data platforms.
• Hands-on expertise with cloud platforms (GCP) and managed services (e.g., Snowflake/BigQuery).
• Strong SQL skills and experience with relational and NoSQL databases.
• Experience with ETL/ELT frameworks (Airflow, dbt).
• Proficiency in Python for data processing and scripting.
• Familiarity with data-modeling techniques (star, snowflake, data-mesh).

Why you'll love working here

• Salary: 1000 $/month